Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

Author:

Kermany Daniel S.,Goldbaum Michael,Cai Wenjia,Valentim Carolina C.S.,Liang Huiying,Baxter Sally L.,McKeown Alex,Yang Ge,Wu Xiaokang,Yan Fangbing,Dong Justin,Prasadha Made K.,Pei Jacqueline,Ting Magdalene Y.L.,Zhu Jie,Li Christina,Hewett Sierra,Dong Jason,Ziyar Ian,Shi Alexander,Zhang Runze,Zheng Lianghong,Hou Rui,Shi William,Fu Xin,Duan Yaou,Huu Viet A.N.,Wen Cindy,Zhang Edward D.,Zhang Charlotte L.,Li Oulan,Wang Xiaobo,Singer Michael A.,Sun Xiaodong,Xu Jie,Tafreshi Ali,Lewis M. Anthony,Xia Huimin,Zhang Kang

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Guangzhou Women and Children’s Medical Center

Guangzhou Regenerative Medicine and Health Guangdong Laboratory

Richard Annesser Fund

Michael Martin Fund

Dick and Carol Hertzberg Fund

Publisher

Elsevier BV

Subject

General Biochemistry, Genetics and Molecular Biology

Reference21 articles.

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3. Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., and Darrell, T. (2013). DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. Proceedings of the 31st International Conference on Machine Learning 32, 647–655.

4. Vascular endothelial growth factor and age-related macular degeneration: from basic science to therapy;Ferrara;Nat. Med.,2010

5. Prevalence of age-related macular degeneration in the United States;Friedman;Arch. Ophthalmol.,2004

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